This research investigates the convergence of chaotic dynamics into stability through the integration of the Chua circuit with another circuit. The combination of these circuits is explored to reveal a dynamic transit...
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This study examines the crucial function that silicon steels, sometimes referred to as electric steels, serve in electromagnetic applications like transformers and motors. The need of preserving ferromagnetic characte...
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In this study, we check the performance of traditional AODV (Ad-hoc On-Demand Distance Vector), MAODV (Multicast AODV), and a proposed Simulated Annealing (SA)-Optimized Routing protocol in a Mobile Ad-hoc Network (MA...
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In this digital age, digital twin technology has been widely applied in various fields. However, its use in agriculture is still in the early stages. Existing literature on plant digital twins indicates that they have...
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In recent times data breaches in various sectors of industry have become a common threat. It has become very crucial to secure patient data in the health industry. The upcoming Healthcare 4.0 techniques can play an im...
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This research investigates the accuracy and loss metrics of many text-to-image synthesis models, such as VQGAN+CLIP, BigGAN, StyleGAN, SR3, Imagen, and Glide. We aim to study these models to discover their ability to ...
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Monitoring the leakage current of surge arrester can find its defects in time, which is of great significance to the security and stability of power system. But the complex environment will increase the difficulty of ...
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It is well known that people who know the presence of network viruses will defend against them, and the more computer viruses are detected and the more measures are taken. However, most previous computer virus propaga...
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Manufacturing companies are exposed to increasingly complex products and shorter product engineering cycles. Unstructured data hinders the integration of knowledge over the different product engineering stages and com...
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Intrusion Detection Systems (IDS) rely heavily on accurate classification of network traffic to identify malicious activity. This paper explores an ensemble learning approach for IDS that prioritizes high recall to mi...
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